Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout

Research output: Contribution to journalArticle

Abstract

Cone-beam CT (CBCT) systems commonly incorporate a flat-panel detector (FPD) with multiplegain readout capability to reduce electronic noise and extend dynamic range. In this work, we report a penalized weighted least-squares (PWLS) method for CBCT image reconstruction with a system model that includes the electronic noise characteristics of FPDs, including systems with dynamic-gain or dual-gain (DG) readout in which the electronic noise is spatially varying. Statistical weights in PWLS were modified to account for the contribution of the electronic noise (algorithm denoted PWLSDG), and the method was combined with a certainty-based approach that improves the homogeneity of spatial resolution (algorithm denoted PWLSDG Cert ). The methods were tested in phantom studies designed to stress DG readout characteristics and translated to a clinical study for CBCT of patients with head traumas. The PWLSDG method demonstrated superior noise-resolution tradeoffs compared to filtered back-projection (FBP) and conventional PWLS. For example, with spatial resolution (edge-spread function width) matched at 0.65 mm, PWLSDG reduced variance by 28%39% and 15%25% compared to FBP and PWLS, respectively. The PWLSDG Cert method achieved more homogeneous spatial resolution than PWLSDG while maintaining similar variance reduction. These findings were confirmed in clinical studies, which showed ~20% variance reduction in peripheral regions of the brain, potentially improving visual image quality in detection of epidural and/or subdural intracranial hemorrhage. The results are consistent with the general notion that incorporating a more accurate system model improves performance in optimization-based statistical CBCT reconstruction-in this case, a more accurate model for (spatially varying) electronic noise to improve detectability of low-contrast lesions.

Original languageEnglish (US)
Article number245018
JournalPhysics in Medicine and Biology
Volume63
Issue number24
DOIs
StatePublished - Dec 14 2018

Keywords

  • cone-beam CT
  • dual-gain
  • electronic noise
  • image quality
  • intracranial hemorrhage
  • model-based iterative reconstruction
  • traumatic brain injury

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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